Authors:
Fabio Clarizia
;
Luca Greco
and
Paolo Napoletano
Affiliation:
University of Salerno, Italy
Keyword(s):
Web search engine, Ontology, Topic model.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Applications of Expert Systems
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Business Analytics
;
Cloud Computing
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Informatics in Control, Automation and Robotics
;
Information Systems Analysis and Specification
;
Intelligent Agents
;
Intelligent Control Systems and Optimization
;
Internet Technology
;
Knowledge Engineering
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Knowledge-Based Systems Applications
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Semantic Web Technologies
;
Sensor Networks
;
Services Science
;
Signal Processing
;
Soft Computing
;
Software Agents and Internet Computing
;
Software Engineering
;
Symbolic Systems
;
Web Databases
;
Web Information Systems and Technologies
Abstract:
In this paper we present a new technique for retrieving relevant web pages in informational queries results. The proposed technique, based on a probabilistic model of language, is embedded in a traditional web search engine. The relevance of aWeb page has been obtained through the judgment of human beings which, referring to continue scale, have assigned a degree of importance to each of the analyzed websites. In order to validate the proposed method a comparison with a classic engine is presented showing comparison based on a measure of Precision and Recall and on a measure of distance with respect to the measure of significance obtained by humans.